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library for simularity identification
Straightforward fuzzy matching, information retrieval and NLP building blocks for JavaScript.
- bloom filter
- canberra
- caverphone
- chebyshev
- cologne
- cosine
- clustering
- daitch-mokotoff
- dice
- fingerprint
- fuzzy
- hamming
- k-means
- jaccard
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Javascript version of hermetrics.py
- hermetrics
- nlp
- similarity metric
- distance metric
- levenshtein
- jaro
- jaro-winkler
- hamming
- osa
- damerau-levenshtein
- jaccard
- dice
N-dimensional distance metrics & K-nearest neighborhoods for point queries
A lightweight, rule-based text similarity calculator that selects the most appropriate comparison algorithm based on input string lengths.
Get Jaccard distance between strings.
Implements the Jaccard algorithm for finding the similarity coefficient between sentences
Grouped One Permutation Hashing (GroupedOPH) implementation for MinHash signature generation.
JSON-Hashify is a library for hashing JSON objects and arrays into compact signatures (sketches) that can be used to compare the similarity of JSON objects.
Promise-based Jaccard similarity coefficient index calculation framework
A Jaccard index calculator supporting multi-set.
Finds measure of similarity/distance between two input sets.
- set
- sorensen
- dice
- jaccard
- ochiai
- otsuka
- barkman
- overlap
- levenshtein
- edit-distance
- euclidean
- distance
- coefficient
- algorithm
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Tanimoto similarity and distance methods
using wuzzy in the real world
TypeScript implementation of the SuperMinHash algorithm for Jaccard similarity estimation
Jaccard Similarity Coefficient Index Stream Transform
An extension of Set meant for checking similarity of strings. Also offers static functions that can be used seperately from the SimilaritySet.
- string-similarity
- similarity-set
- similarity
- strings
- similar
- difference
- compare
- comparison
- dice
- levensthein
- jaccard
calculate jaccard index for two sorted streams of data
Very simple package for measuring the similarity of two sets by their shared members.
This package adds new features to the mongodb database through the use of fuzzy techniques and approximate string matching.